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A high-density genetic map and QTL mapping on growth and latex yield-related traits in Hevea brasiliensis Müll.Arg

Authors :
Zewei An
Yanhong Zhao
Xiaofei Zhang
Yanshi Hu
Xiaolong Li
Huasun Huang
Xiao Huang
Han Cheng
Source :
Industrial Crops and Products. 132:440-448
Publication Year :
2019
Publisher :
Elsevier BV, 2019.

Abstract

Hevea brasiliensis Mull.Arg., the rubber tree, is an important industrial crop, which is the major source of nature rubber. Recently, Simple Sequence Repeat (SSR)- and Single Nucleotide Polymorphism (SNP)-based genetic maps have been reported, however further trait-related markers are needed for efficient molecular breeding in rubber tree. In this study, a total of 206 F1 progeny derived from a cross of CATAS 8–79 × MT/C/11 9/67 were sequenced and genotyped by specific–locus amplified fragment sequencing (SLAF-seq) technology. Based on 268,592 SNPs obtained from SLAF-seq, a high-density genetic map with 4,543 SNPs was constructed, covering 2,670.27 cM of the whole rubber tree genome. This map has an average marker distance of 0.59 cM. Based on the high-density genetic map, dynamic quantitative trait loci (QTL) analysis of latex yield and stem growth was carried out by conditional and unconditional QTL mapping. To our knowledge, it is the first time to perform conditional QTL mapping of rubber tree for exploring QTLs expressed selectively at different growth stages. In total, eleven QTLs for stem growth and 12 QTLs for latex yield, distributing in 15 linkage groups (LGs), were detected, explaining 3.1%–18.4% of the phenotypic variance. Two QTLs, qSG-8-2 for stem growth and qLD-8-3 for latex yield, were mapped within the same marker interval of LG 8 with a genetic distance of 3.0 cM. Herein the high-density genetic map and trait-related QTLs in rubber tree were reported, which will facilitate the genetic research of rubber tree and enhance rubber tree molecular breeding.

Details

ISSN :
09266690
Volume :
132
Database :
OpenAIRE
Journal :
Industrial Crops and Products
Accession number :
edsair.doi...........1352692ad59a4d1772b993eae42941f0
Full Text :
https://doi.org/10.1016/j.indcrop.2019.03.002